Embodiments of the present invention relate generally to methods and systems for determining a level of expertise of a potential subject matter expert and more particularly to assessing and scoring user proficiency in topics determined by data from social networks and other sources.
Social networks and other networks or systems, such as a corporation's Intranet and/or Human Capital Management (HCM) system for example, can have a wealth of data about people and their skill-sets. For example, a user can define a social network profile in which can be identified various skills, experience, training, etc. that user claims to have. In some cases, other users can endorse or otherwise indicate agreement or support for those claimed skills or may indicate other, additional skills for the user. In the case of an HCM system, an employee's resume, educational and/or training history, work experience, and/or other information can be maintained. This data can be used to determine for which topics and/or skills a user claims proficiency in. However, this information may need to be confirmed and claimed skills for a particular individual or set of individuals may be scored before it is relied upon in some way.
Current solutions for proficiency scoring rely on direct models, namely, users endorsing themselves and each other on topics that the users claim for themselves or others. For example, the more endorsements for a given skill, the more proficient the user is considered to be. However, and especially with social networks, rather than being proficient, the user may simply be popular among a group of peers. HCM systems also often allow users to self-assess, take exams, or be assessed, for example, their manager or peers, all of which can provide a rating for that individual on a particular skill. While more such information may be more reliable than peer endorsements on a social network, it is also limited to the explicitly defined skill and does not consider similar or related skills that the user may also be considered proficient in. Hence, there is a need for improved methods and systems for determining a level of expertise of a potential subject matter expert.